Gene expression profiling of HepG_(2) cells after treatment with black tea polyphenols

This study aimed to determine the effects of black tea polyphenols on gene expression in hepatocellular cancer cells.The total RNA from HepG_(2) hepatocellular cancer cells treated with black tea polyphenols was subjected to Human 14K cDNA microarray analysis.Real-time PCR and Western blot analysis were conducted to verify microarray data.Black tea polyphenols treatment at the dose of 20 mg/L,40 mg/L or 80 mg/L for one to three days inhibited the growth of HepG_(2) cells in a dose and time dependent manner.A total of 48 genes showed more than two-fold change after black tea polyphenols treatment,including 17 upregulated genes and 31 downregulated genes,and they were involved in the regulation of cell growth,cell cycle,apoptosis,signaling,angiogenesis,tumor invasion and metastasis.Real-time PCR analysis of the selected genes showed that their mRNA expression changes were consistent with the microarray data.In addition,Western blot analysis of the selected genes showed that their protein expression changes were consistent with mRNA expression.In conclusion,gene expression profiles provide comprehensive molecular mechanisms by which black tea polyphenols exerts growth inhibition effects on cancer cells.The novel molecular targets identified in this study may be further exploited as therapeutic strategies for hepatocellular cancer.

SuperFeat:Quantitative Feature Learning from Single-cell RNA-seq Data Facilitates Drug Repurposing

In this study,we devised a computational framework called Supervised Feature Learning and Scoring(SuperFeat)which enables the training of a machine learning model and evaluates the canonical cellular statuses/features in pathological tissues that underlie the progression of disease.This framework also enables the identification of potential drugs that target the presumed detrimental cellular features.This framework was constructed on the basis of an artificial neural network with the gene expression profiles serving as input nodes.The training data comprised single-cell RNA sequencing datasets that encompassed the specific cell lineage during the developmental progression of cell features.A few models of the canonical cancer-involved cellular statuses/features were tested by such framework.Finally,we illustrated the drug repurposing pipeline,utilizing the training parameters derived from the adverse cellular statuses/features,which yielded successful validation results both in vitro and in vivo.SuperFeat is accessible at https://github.com/weilin-genomics/rSuperFeat.

基于公共数据库分析NPY1R在乳腺癌中的表达及与他莫昔芬耐药的关系

目的 :研究NPY1R在乳腺癌他莫昔芬耐药中的作用,为预测和逆转乳腺癌内分泌耐药提供新的分子标志物。方法 :从GEO数据库中获取乳腺癌他莫昔芬耐药前后基因表达数据集,并通过GEO2R筛选出NPY1R为乳腺癌他莫昔芬耐药前后差异表达基因,利用TCGA数据库和CPTAC数据库分析NPY1R在乳腺癌组织中的mRNA和蛋白表达水平,收集我院临床组织样本并通过免疫组化验证NPY1R在他莫昔芬耐药前后的配对组织中的差异,通过STRING数据库构建NPY1R编码蛋白互作网络并进行GO/KEGG分析以及利用starBase数据库预测靶向作用于NPY1R的miRNAs;最后使用Kaplan-Meier Plotter数据库分析NPY1R在乳腺癌患者中的生存及预后。结果 :与正常组织比较,NPY1R在乳腺癌中mRNA表达下调且其编码蛋白表达水平也同样降低;免疫组化结果显示NPY1R在乳腺癌他莫昔芬耐药后复发组织中表达下降;临床相关性分析发现NPY1R的表达与乳腺癌中ER、PR、Her2状态显著相关;GO/KEGG分析显示NPY1R及其相关蛋白主要作用于G蛋白偶联受体等信号通路,star Base预测mi RNA-224-5p和miRNA-212-3p可能靶向作用于NPY1R;通过生存分析发现低表达NPY1R基因的乳腺癌患者伴随着较差的预后。结论 :NPY1R为他莫昔芬耐药的相关基因,其表达下调可能与乳腺癌细胞产生他莫昔芬药物抵抗相关,有效发掘这些内分泌治疗耐药相关差异表达基因中的数据信息,为乳腺癌内分泌抵抗提供新的治疗方向。